We trained our TBVE model and HifiGAN vocoder [1]} on an internal dataset of 378 hours of clean speech data from 95 speakers with a variety of US English accents. We evaluated our systems on 4 unseen speakers (2 male and 2 female). Using a pretrained speaker verification system, we extracted 32-dimensional utterance embeddings from each utterance, and calculated speaker embeddings by averaging all the utterance embeddings for a given speaker.
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